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Calculation (0, 2016-06-05)
Calculation\SQL_retrieve.m (21221, 2016-06-05)
Calculation\SQL_store.m (12565, 2016-06-05)
Calculation\TS_CalculateFeatureVector.m (12893, 2016-06-05)
Calculation\TS_LinkOperationsWithMasters.m (2721, 2016-06-05)
Calculation\TS_WhichProblemTS.m (2600, 2016-06-05)
Calculation\TS_combine.m (14030, 2016-06-05)
Calculation\TS_compute.m (9595, 2016-06-05)
Calculation\TS_compute_masterloop.m (2097, 2016-06-05)
Calculation\TS_compute_oploop.m (3055, 2016-06-05)
Calculation\TS_init.m (5510, 2016-06-05)
Calculation\sample_runscript_matlab.m (3059, 2016-06-05)
Calculation\sample_runscript_sql.m (3317, 2016-06-05)
Database (0, 2016-06-05)
Database\INP_mops.txt (59416, 2016-06-05)
Database\INP_ops.txt (698912, 2016-06-05)
Database\INP_ops_reduced.txt (22706, 2016-06-05)
Database\SQL_ChangeDatabase.m (3175, 2016-06-05)
Database\SQL_FlushKeywords.m (6678, 2016-06-05)
Database\SQL_GiveMeCode.m (2404, 2016-06-05)
Database\SQL_ShowConnSettings.m (2282, 2016-06-05)
Database\SQL_TableCreateString.m (5705, 2016-06-05)
Database\SQL_add.m (38025, 2016-06-05)
Database\SQL_add_chunked.m (2799, 2016-06-05)
Database\SQL_clear_remove.m (11654, 2016-06-05)
Database\SQL_closedatabase.m (1253, 2016-06-05)
Database\SQL_create_all_tables.m (3402, 2016-06-05)
Database\SQL_create_db.m (5206, 2016-06-05)
Database\SQL_getids.m (12261, 2016-06-05)
Database\SQL_opendatabase.m (2466, 2016-06-05)
Database\SQL_reset.m (3582, 2016-06-05)
Database\install_jconnector.m (5026, 2016-06-05)
Database\mysql-connector-java-5.1.35-bin.jar (968670, 2016-06-05)
Database\mysql_dbexecute.m (1815, 2016-06-05)
Database\mysql_dbopen.m (4155, 2016-06-05)
Database\mysql_dbquery.m (2934, 2016-06-05)
Operations (0, 2016-06-05)
Operations\COPYING.txt (35147, 2016-06-05)
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# *hctsa*, a highly comparative time-series analysis code repository *hctsa* is a software package for running highly comparative time-series analysis, using [Matlab](www.mathworks.com/products/matlab/) (full support for versions R2014b or later; for use in python cf. [pyopy](https://github.com/strawlab/pyopy)). The software provides a code framework that allows thousands of time-series analysis features to be extracted from time series (or a time-series dataset), as well as tools for normalizing and clustering the data, producing low-dimensional representations of the data, identifying discriminating features between different classes of time series, learning multivariate classification models using large sets of time-series features, finding nearest matches to a time series of interest, and a range of other visualization and analysis functionality. All of these types of analysis are described in our accompanying [open access journal article](http://rsif.royalsocietypublishing.org/content/10/83/20130048.full). Comprehensive documentation for *hctsa* is provided [on gitbook](https://www.gitbook.com/book/benfulcher/highly-comparative-time-series-analysis-manual/details), which can be read online or downloaded in a pdf, epub, or mobi format. Any feedback is hugely helpful ([email me](mailto:ben.d.fulcher@gmail.com)) and, in particular, any improvements to the code would be _much_ appreciated in the form of [issues](https://github.com/benfulcher/hctsa/issues) or [pull requests](https://help.github.com/articles/using-pull-requests/). ### Downloading the repository For users unfamiliar with git, the current version of the repository can be downloaded by simply clicking the *Download .zip* button. It is recommended to use the repository with git. For this, please [make a fork](https://help.github.com/articles/fork-a-repo/) of it, clone it to your local machine, and then set an [upstream remote](https://help.github.com/articles/fork-a-repo/#step-3-configure-git-to-sync-your-fork-with-the-original-spoon-knife-repository) to keep it synchronized with the main repository e.g., using the following code: ``` git remote add upstream git://github.com/benfulcher/hctsa.git ``` (make sure that you have [generated an ssh key](https://help.github.com/articles/generating-ssh-keys/) and associated it with your github account). You can then update to the latest stable version of the repository by pulling the master branch to your local repository: ``` git pull upstream master ``` For analyzing specific datasets, we recommend working outside of the repository so that incremental updates can be pulled from the upstream repository. Details on how to merge the latest version of the repository with the local changes in your fork can be found [here](https://help.github.com/articles/syncing-a-fork/). ## *hctsa* licenses ### Internal licenses There are two licenses applied to the core parts of the repository: 1. Sections of the repository required to compute features from time-series data is licensed as [GNU General Public License version 3](http://www.gnu.org/licenses/gpl-3.0.en.html). 2. Sections implementing the framework for running *hctsa* analyses and visualizations is licensed as the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/). To use this portion of the code for commercial use, please contact [Ben Fulcher](ben.d.fulcher@gmail.com). A range of external code packages are provided in the **Toolboxes** directory of the repository, and each have their own associated license (see below). ### External packages and dependencies The following [Matlab toolboxes](https://mathworks.com/programs/nrd/matlab-toolbox-price-request.html?ref=ggl&s_eid=ppc_18665571802&q=matlab%20toolboxes%20price) are used by *hctsa* and are required for full functionality of the software. In the case that some toolboxes are unavailable, the *hctsa* software can still be used, but only a reduced set of time-series features will be computed. 1. Statistics Toolbox 2. Signal Processing Toolbox 3. Curve Fitting Toolbox 4. System Identification Toolbox 5. Wavelet Toolbox 6. Econometrics Toolbox --- The following time-series analysis packages are provided with the software (in the **Toolboxes** directory), and are used by our main feature extraction algorithms to compute meaningful structural features from time series: * [*TISEAN* package for nonlinear time-series analysis, version 3.0.1](http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/index.html) (GPL license). * [*TSTOOL* package for nonlinear time-series analysis, version 1.2](http://www.dpi.physik.uni-goettingen.de/tstool/) (GPL license). * Joseph T. Lizier's [Java Information Dynamics Toolkit (JIDT)](https://github.com/jlizier/jidt) for studying information-theoretic measures of computation in complex systems, version 1.3 (GPL license). * Time-series analysis code developed by [Michael Small](http://staffhome.ecm.uwa.edu.au/~00027830/code.html) (unlicensed). * Max Little's [Time-series analysis code](http://www.maxlittle.net/software/index.php) (GPL license). * Sample Entropy code from [Physionet](http://www.physionet.org/faq.shtml#license) (GPL license). * [*ARFIT* Toolbox for AR model estimation](http://climate-dynamics.org/software/#arfit) (unlicensed). * [*gpml* Toolbox for Gaussian Process regression model estimation, version 3.5](http://www.gaussianprocess.org/gpml/code/matlab/doc/) (FreeBSD license). * Danilo P. Mandic's [delay vector variance code](http://www.commsp.ee.ic.ac.uk/~mandic/dvv.htm) (GPL license). * [Cross Recurrence Plot Toolbox](http://tocsy.pik-potsdam.de/CRPtoolbox/) (GPL license) * Zoubin Ghahramani's [Hidden Markov Model (HMM) code](http://mlg.eng.cam.ac.uk/zoubin/software.html) (MIT license). * Danny Kaplan's Code for embedding statistics (GPL license). * Two-dimensional histogram code from Matlab Central (BSD license). * Various histogram and entropy code by Rudy Moddemeijer (unlicensed). ## Citation and Acknowledgements If you use this software, please read and cite the (open-access) work published as: B. D. Fulcher, M. A. Little, N. S. Jones (2013) [Highly comparative time-series analysis: the empirical structure of time series and their methods](http://rsif.royalsocietypublishing.org/content/10/83/20130048.full). *J. Roy. Soc. Interface* **10**, 83. See also our open access IEEE TKDE paper on [feature-based time-series classification](http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=678***25) and an application of these ideas to [fetal heart rate analysis](http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6346629). Many thanks go to [Romesh Abeysuriya](https://github.com/RomeshA) for helping with the mySQL database set-up and install scripts, and [Santi Villalba](https://github.com/sdvillal) for lots of helpful feedback and advice on the software. ## Related resources ### pyopy This excellent repository allows users to run *hctsa* software from within python: [pyopy](https://github.com/strawlab/pyopy). ### Comp-Engine Time Series An accompanying web resource for this project is [Comp-Engine Time Series](http://www.comp-engine.org/timeseries), which allows users to compare thousands of diverse types of time-series analysis code and time-series data. Note that the code files on Comp-Engine Time Series are based on an early implementation and rarely match with the updated features and functions contained in this repository. ### Other time-series analysis software packages * A python-based nonlinear time-series analysis and complex systems code package, [pyunicorn](http://scitation.aip.org/content/aip/journal/chaos/25/11/10.1063/1.4934554).

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